DWSI: AN APPROACH TO SOLVING THE POLYGON INTERSECTION-SPREADING PROBLEM WITH A PARALLEL UNION ALGORITHM AT THE FEATURE LAYER LEVEL

A dual-way seeds indexing (DWSI) method based on R-tree and the OpenGeospatial Consortium (OGC) simple feature model was proposed to solve the polygon intersection-spreading problem. The parallel polygon union algorithm based on the improved DWSI and the OpenMP parallel programming model was developed to validate the usability of the data partition method. The experimental results reveal that the improved DWSI method can implement a robust parallel task partition by overcoming the polygon intersection-spreading problem. The parallel union algorithm applied DWSI not only scaled up the data processing but alsospeeded up the computation compared with the serial proposal, and it showed ahigher computational efficiency with higher speedup benchmarks in the treatment of larger-scale dataset. Therefore, the improved DWSI can be a potential approach to parallelizing the vector data overlay algorithms based on the OGC simple data model at the feature layer level

Modeling and Analyzing User Behavior Risks in Online Shopping Processes Based on Data-Driven and Petri-Net Methods

With the rapid spread of e-commerce and e-payment, the increasing number of people choose online shopping instead of traditional buying way. However, the malicious user behaviors have a significant influence on the security of users' accounts and property. In order to guarantee the security of shopping environment, a method based on Complex Event Process (CEP) and Colored Petri nets (CPN) is proposed in this paper. CEP is a data-driven technology that can correlate and process a large amount of data according to Event Patterns, and CPN is a formal model that can simulate and verify the specifications of the online shopping processes. In this work, we first define the modeling scheme to depict the user behaviors and Event Patterns of online shopping processes based on CPN. The Event Patterns can be constructed and verified by formal methods, which guarantees the correctness of Event Patterns. After that, the Event Patterns are translated into Event Pattern Language (EPL) according to the corresponding algorithms. Finally, the EPLs can be inserted into the complex event processing engine to analyze the users' behavior flows in real-time. In this paper, we validate the effectiveness of the proposed method through case studies

DWSI: AN APPROACH TO SOLVING THE POLYGON INTERSECTION-SPREADING PROBLEM WITH A PARALLEL UNION ALGORITHM AT THE FEATURE LAYER LEVEL

A dual-way seeds indexing (DWSI) method based on R-tree and the OpenGeospatial Consortium (OGC) simple feature model was proposed to solve the polygon intersection-spreading problem. The parallel polygon union algorithm based on the improved DWSI and the OpenMP parallel programming model was developed to validate the usability of the data partition method. The experimental results reveal that the improved DWSI method can implement a robust parallel task partition by overcoming the polygon intersection-spreading problem. The parallel union algorithm applied DWSI not only scaled up the data processing but alsospeeded up the computation compared with the serial proposal, and it showed ahigher computational efficiency with higher speedup benchmarks in the treatment of larger-scale dataset. Therefore, the improved DWSI can be a potential approach to parallelizing the vector data overlay algorithms based on the OGC simple data model at the feature layer level

Effect of Zn doping on magnetic order and superconductivity in LaFeAsO

We report Zn-doping effect in the parent and F-doped LaFeAsO oxy-arsenides. Slight Zn doping in LaFe$_{1-x}$Zn$_{x}$AsO drastically suppresses the resistivity anomaly around 150 K associated with the antiferromagnetic (AFM) spin density wave (SDW) in the parent compound. The measurements of magnetic susceptibility and thermopower confirm further the effect of Zn doping on AFM order. Meanwhile Zn doping does not affect or even enhances the $T_c$ of LaFe$_{1-x}$Zn$_{x}$AsO$_{0.9}$F$_{0.1}$, in contrast to the effect of Zn doping in high-$T_c$ cuprates. We found that the solubility of Zn content ($x$) is limited to less than 0.1 in both systems and further Zn doping (i.e., $x$ $\geq$ 0.1) causes phase separation. Our study clearly indicates that the non-magnetic impurity of Zn$^{2+}$ ions doped in the Fe$_2$As$_2$ layers affects selectively the AFM order, and superconductivity remains robust against the Zn doping in the F-doped superconductors.Comment: 7 figures, 13 pages; revised version with more dat

Pressure induced superconductivity bordering a charge-density-wave state in NbTe4 with strong spinorbit coupling

Transition-metal chalcogenides host various phases of matter, such as charge-density wave (CDW), superconductors, and topological insulators or semimetals. Superconductivity and its competition with CDW in low-dimensional compounds have attracted much interest and stimulated considerable research. Here we report pressure induced superconductivity in a strong spin-orbit (SO) coupled quasi-one-dimensional (1D) transition-metal chalcogenide NbTe$_4$, which is a CDW material under ambient pressure. With increasing pressure, the CDW transition temperature is gradually suppressed, and superconducting transition, which is fingerprinted by a steep resistivity drop, emerges at pressures above 12.4 GPa. Under pressure $p$ = 69 GPa, zero resistance is detected with a transition temperature $T_c$ = 2.2 K and an upper critical field $H_{c2}$= 2 T. We also find large magnetoresistance (MR) up to 102\% at low temperatures, which is a distinct feature differentiating NbTe$_4$ from other conventional CDW materials.Comment: https://rdcu.be/LX8

Single nonmagnetic impurity resonance in FeSe-based 122-type superconductors as a probe for pairing symmetry

We study the effect of a single non-magnetic impurity in A$_{y}$Fe$_{2-x}$Se$_{2}$ (A=K, Rb, or Cs) superconductors by considering various pairing states based on a three-orbital model consistent with the photoemission experiments. The local density of states on and near the impurity site has been calculated by solving the Bogoliubov-de Gennes equations self-consistently. The impurity-induced in-gap bound states are found only for attractive impurity scattering potential, as in the cases of doping of Co or Ni, which is characterized by the strong particle-hole asymmetry, in the nodeless $d_{x^2-y^2}$ wave pairing state. This property may be used to probe the pairing symmetry of FeSe-based 122-type superconductors.Comment: 7 pages, 7 figure

Modeling and Analyzing User Behavior Risks in Online Shopping Processes Based on Data-Driven and Petri-Net Methods

With the rapid spread of e-commerce and e-payment, the increasing number of people choose online shopping instead of traditional buying way. However, the malicious user behaviors have a significant influence on the security of users’ accounts and property. In order to guarantee the security of shopping environment, a method based on Complex Event Process (CEP) and Colored Petri nets (CPN) is proposed in this paper. CEP is a data-driven technology that can correlate and process a large amount of data according to Event Patterns, and CPN is a formal model that can simulate and verify the specifications of the online shopping processes. In this work, we first define the modeling scheme to depict the user behaviors and Event Patterns of online shopping processes based on CPN. The Event Patterns can be constructed and verified by formal methods, which guarantees the correctness of Event Patterns. After that, the Event Patterns are translated into Event Pattern Language (EPL) according to the corresponding algorithms. Finally, the EPLs can be inserted into the complex event processing engine to analyze the users’ behavior flows in real-time. In this paper, we validate the effectiveness of the proposed method through case studies